All of the proposals for building safe AI outlined in [1]} explicitly call for adversarial robustness and/or interpretability tools.
Finding and fixing potentially hazardous bugs and biases in advanced AI systems will hinge on interpretability, adversaries, and adversarial training.
Consequently, continued work toward scalable techniques for interpretability and identifying vulnerabilities will be important for safer AI.
